Method of determining an image distribution for a light field data structure

ABSTRACT

The invention relates to a method of determining an image distribution (D opt ) for a light field data structure, which method comprises obtaining a plurality of images (F 1 , F 2 , . . . , F n ) from a plurality of image sources (C 1 , C 2 , . . . , C n ), performing image analysis on each image (F 1 , F 2 , . . . , F n ) of the plurality of images (F 1 , F 2 , . . . , F n ) to determine whether a specified criterion is satisfied by the content of that image (F 1 , F 2 , . . . , F n ), and identifying a group ( 12 ) of images (F 1 , F 2 , . . . , F n ) whose contents satisfy the specified criterion. The image group ( 12 ) is compared to each reference image distribution (D 1 , D 2 , . . . , D m ) of a set of predefined reference image distributions (D 1 , D 2 , . . . , D m ,) to select an optimal image distribution (D opt ), wherein a reference image distribution (D 1 , D 2 , . . . , D m ) comprises a predefined arrangement of I-images and P-images of the light field data structure. Each image (F 1 , F 2 , . . . , F n ) of the plurality of images (F 1 , F 2 , . . . , F n ) of the light field data structure is subsequently designated to be either an I-image or a P-image according to the selected image distribution (D opt ). The invention also describes a system ( 1 ) for determining an image distribution (D opt ) for a light field data structure.

FIELD OF THE INVENTION

The invention relates to a method of determining an image distributionfor a light field data structure. The invention further relates to asystem for determining a image distribution for a light field datastructure.

BACKGROUND OF THE INVENTION

Light-field rendering has gained in importance in recent years withcontinuing advances in the field of image processing and computergraphics. With light field rendering, photo-realistic views of scenescan be created using previously digitised images, whether these imageshave been artificially created or are images of actual scenes, capturedby a camera. For instance, a light field can be generated from athree-dimensional model of a scene, or can be created using images of anactual scene, for example, images taken by an arrangement of cameraspositioned about the scene. All the images of a scene, taken at a singleinstant, are collectively referred to as a ‘light-field data structure’.A description of light field rendering is given by the paper “LightField Rendering” (SIGGRAPH May 1996, Marc Levoy and Pat Hanrahan). Somewell-known movies successfully combine traditional camera recording withcomputer-aided light-field rendering to generate complex but realisticspecial effects.

Light fields can be captured photographically using, for example, ahand-held camera, a remote-controlled camera, or an array of camerasmounted on a structure such as a gantry. FIG. 1 shows such anarrangement of cameras C, where the cameras are grouped to surround anarea A of interest. For the sake of clarity, only a few cameras areshown. In reality, images must be generated from quite a large number ofcameras, or viewpoints, for photo-realistic three-dimensional renderingof a scene. This leads to the problem of storage or transmission for thelarge number of images, since storage space and transmission bandwidthare expensive resources.

To store or transmit the images in a cost-effective way, the images canbe compressed using some method of lossy data compression, which resultsin a loss of image quality that is, however, not noticeable to theviewer. An image compressed or coded using a lossy data compressionalgorithm can be represented using fewer bits. Several such lossycompression techniques are known. For example, the most common methodused for lossy image compression is transform coding, in which aFourier-related transform such as the Discrete Cosine Transform (DCT) isapplied to the image data. One common standard for image (and audio)compression is the MPEG-2 (Motion Pictures Expert Group)

An image or frame that is compressed in its entirety, i.e. without usinginformation obtained from other images, is often referred to as an‘intra-coded image’, ‘intraimage’, ‘I-image’, or ‘I-frame’. Since theentire image or frame is compressed, this can be rendered again to afairly high level of quality. However, even more bandwidth can be savedby making use of the fact that picture data in a sequence of images isoften redundant. For example, a part of each frame, such as the sky, canremain the same over a sequence of frames. Evidently, this part of eachimage in the image sequence need only be coded once, and only thoseparts of an image that have changed with respect to a reference imageneed be coded. This type of compression is known as ‘interframecompression’ or ‘predictive coding’, and an image compressed in this wayis referred to as an ‘interimage’, ‘P-image’ or ‘P-frame’. A P-image canbe coded using a previous image (an I-image or a P-image) captured bythe same camera. It has been shown that a good picture quality (from theviewer's point of view) can be obtained by using a compression schemefor a light-field data structure based on a trade-off betweenhigh-quality (I-images) and low cost (P-images), in which some of theimages are compressed as I-images and the remainder are compressed asP-images. In order to obtain a certain level of quality in rendering,however, the I-images should be evenly distributed over the light-fielddata structure, which can be understood to be a virtual arrangement ofthe images. FIG. 2 a shows an example of such a compression scheme.Here, every second image in every second row of the light-field datastructure is an I-image, as indicted by the letter “I”, and theremainder of the images are coded as P-images, as indicated by theletter “P”. FIG. 2 b shows another possible compression scheme. Atechnique for data compression using I-images and P-images is describedin the paper “Data Compression for Light-Field Rendering” (Marcus Magnorand Bernd Girod, IEEE Transactions on Circuits and Systems for VideoTechnology, Vol. 10, No. 3, April 2000).

In some image rendering applications, for example an interactive 3-Dvideo application, it may be that some object or item is considered tobe of particular importance, for example the football in a footballmatch. Usually, the viewer's attention would be focused on the ball. Ina 3-D interactive video application rendered using images captured asdescribed above, the user would likely want to have the scenes renderedso that this “important object” is the centre of attention. However,state-of-the-art techniques of light-field data compression do not adaptto such considerations. Using the known techniques, a certaincompression scheme is chosen, for example the scheme shown in FIG. 2 a,and all the light-field data structures are coded using this scheme,regardless of which images would in fact be most suited for intraimageor interimage compression. Therefore, an ‘unfavourable’ compressionscheme, in which the important object is not coded using a sufficientnumber of I-images, might lead to a noticeable deficiency in the qualityof the rendered scenes.

OBJECT AND SUMMARY OF THE INVENTION

Therefore, it is an object of the invention to provide an improved wayof performing video image data compression.

To this end, the present invention provides a method of determining animage distribution for a light field data structure, which methodcomprises obtaining a plurality of images from a plurality of imagesources, performing image analysis on each image of the plurality ofimages to determine whether a specified criterion is satisfied by thecontent of that image, and determining a group of images whose contentsatisfies the specified criterion. This image group is then compared toeach reference image distribution of a set of predefined reference imagedistributions, wherein a reference image distribution comprises apredefined arrangement of I-images and P-images of the light field datastructure, to select an optimal image distribution. Each image of theplurality of images of the light field data structure is then designatedto be either an I-image or a P-image according to the selected imagedistribution.

The image sources used to obtain the plurality of images can be an arrayof cameras, arranged about a target scene. The number of camerasdetermines the dimensions of the light-field data structure. Forexample, a total of sixty-four cameras can capture sixty-four images atany instant, and these can be virtually arranged in an 8×8 array orlight-field data structure for that instant. The cameras can be mountedon one or more gantries, or can be attached to a support. It is alsopossible for some or all of the cameras to be moveable, for examplebeing handheld or remote controlled.

An obvious advantage of the method according to the invention is that ahigh level of quality for a future interactive application can beobtained with relatively little computational effort and without anyadditional storage or transmission requirements. With the methodaccording to the invention, as many images as possible containing a“relevant object” are coded to a high level of quality for each of asequence of light-field data structures that are used at a later stagein rendering three-dimensional scenes. There can be any number ofpredefined reference image distributions available to which theimage-related array can be compared. In each comparison, the mostsuitable reference image distribution is chosen, so that, for eachlight-field data structure, as many images as possible containing therelevant object are coded as high-quality intraimages, or I-images.

An appropriate system for determining an image distribution for a lightfield data structure comprises a plurality of image sources forobtaining a plurality of images, and an image analysis module forperforming image analysis on each image of the plurality of images todetermine whether a specified criterion is satisfied by the content ofthat image. The system further comprises an image group identificationmodule for identifying a group of images whose contents satisfy thespecified criterion, and also a comparison module for comparing theimage group to each reference image distribution of a set of predefinedreference image distributions to select an optimal reference imagedistribution, wherein a reference image distribution comprises apredefined arrangement of I-images and P-images of the light field datastructure, and an image designation module for designating each image ofthe plurality of images of the light field data structure to be eitheran I-image or a P-image on the basis of the selected image distribution.

The dependent claims and the subsequent description discloseparticularly advantageous embodiments and features of the invention.

Since the method according to the invention is concerned with optimisingthe quality of a rendered scene from one or more different viewpointsfocused on an important object or object of relevance, the specifiedcriterion preferably comprises descriptive parameters related to anobject that can appear in the image, i.e. as part of the content of theimage. In the example already given, the relevant object might be theball in a football game or any other such type of ball game. Anotherexample of an object of relevance might be the lead cyclist in a cyclerace or the singer on stage in a concert. The ‘object of interest’,often referred to as a ‘region of interest’ or ROI for short, can beidentified in an initial image using known techniques and a graphicaluser interface. For example, a camera operator at a football match canidentify the football in one of the initial images captured by one ofthe cameras as recording commences, or he might use existing videofootage to identify the ball. He can then specify the criterion in asuitable manner, for example by a command such as “image must containthis object”. Subsequently, the graphical user interface can generatedescriptive parameters for this criterion and forward these parametersto all image analysis units of all cameras. Since each image for eachlight-field data structure must be analysed, it is advantageous for eachcamera to be equipped with an image analysis unit for performing thenecessary image analysis steps.

Alternatively, the important object can be filmed by a dedicated camera,where this dedicated camera continually tracks the object duringfilming. The dedicated camera can be one of the array of cameras, or canbe an additional camera. The object that is located in the centre ofthis camera's field of vision can be defined to be the relevant object.Therefore, if the camera stops tracking the object, for instance thefootball, and commences tracking another object, for instance thereferee or another player, this change can be noted by image processingsoftware. Suitable parameters describing the current relevant object inthe image content can then be generated and forwarded to the othercameras.

In the method according to the invention, the images captured thereafterby the cameras are analysed to determine whether their contents satisfythe specified criterion. Generally, it is easiest to determine whetheran image contains relevant object or region of interest by subjectingthe image to a process known as segmentation. Therefore, the step ofperforming image analysis on an image preferably comprises running asegmentation algorithm on that image. Such image processing techniquesfor determining whether a relevant object is visible in an image, i.e.whether a specified criterion is satisfied or not, will be known to aperson skilled in the art, and need not be discussed in detail here. Anexample of such an approach to image analysis is laid out in the paper“Pattern Tracking and 3-D Motion Reconstruction of a Rigid Body From a2-D Image Sequence” (Dasgupta and Banerjee, IEEE Transactions onSystems, Man, and Cybernetics—Part C: Applications and Reviews, Vol. 35,No. 1, February 2005).

The results of the image processing yield a group of images whosecontents satisfy the specified criterion (e.g. images show the ball),while the contents of the remaining images do not satisfy the specifiedcriterion (e.g. images do not show the ball). Since it is known whichimage originated from which camera, this image group can preferably becompiled as an image-related array based, for example, on the presenceor absence of the object of interest in the images. This image-relatedarray can be a simple one-dimensional array, for example comprising aseries of binary values, and overwritten or updated for each newlight-field data structure. Each bit of the image-related array can beassociated with a particular camera. For example, the twelfth bit in thearray can be set to “1” if the image from the twelfth camera for thecurrent light-field data structure contains the object of interest, orcan be set to “0” if the object of interest is not visible in thatimage.

Once the image group or image-related array has been compiled for thecurrent set of images, this can be compared to all available referenceimage distributions in order to select the most suitable distribution. Areference image distribution has been shown with a graphicalrepresentation in FIG. 2 a. In reality, an image distribution mightsimply comprise another one-dimensional array, with a sequence of bitseach associated with a video coder. The image distribution forsixty-four images visualised in FIG. 2 a might therefore actually takethe following form, where the vector or array has 64 entries:D₁={P,P,P,P,P,P,P,P,P,I,P,I,P,I,P,I,P,P,P, . . . , P,P}

It follows that a comparison between the image-related array and areference image distribution is reduced to a simple one-to-onecomparison of the relevant vectors. The comparison resulting in the mostmatches (i.e. the most “1” and “I” pairs) can then result in selectingthat reference image distribution for the current light-field datastructure. Therefore, in a particularly preferred embodiment of theinvention, the optimal image distribution corresponds to the referenceimage distribution which provides the greatest number of I-images forthe image group. Obviously, if two or more reference image distributionsyield the highest number of matches, any one of these reference imagedistributions can be chosen to be the optimal image distribution. Whichof theses reference image distributions to use may then be chosen usinga further criterion, for example to simply use the previous referenceimage distribution if this is one of the reference image distributionsidentified by the comparison.

In the method according to the invention, the images for the currentlight-field data structure are then designated to be coded as eitherintraframes (I-images) or interframes (P-images). In a particularlyadvantageous approach, the vector representing the optimal imagedistribution can be simply translated to a vector giving the image typedesignations for each image. Again, a simple “1” or “0” can suffice todesignate an image as an intraframe or interframe image. For example, a“1” can mean “code this image as an intraframe image”, and a “0” canmean “code this image as an interframe image”. Therefore, in thisadvantageous approach, each “I” entry of the selected image distributionneed simply be converted to “1”, and each “P” entry need simply beconverted to “0” to provide each image with its image designation forthe current light-field data structure.

To perform video coding of a light field data structure using the methodaccording to the invention, each designated I-image is coded using acompression algorithm, for example a discrete cosine transform (DCT)compression algorithm or a wavelet compression algorithm, and eachP-image is coded using one or more previously coded P-images orI-images. Each frame or image is coded by a video coder that can performeither intraframe or interframe coding, as required. The imagedesignator accompanying the image is preferably used to decide whichcoder to apply. The choice of compression algorithm, as will be known toa person skilled in the art, may be dictated by standards, for exampleMPEG-2, or may be chosen freely, depending on the application.

The steps of the method described above can be carried out byappropriate digital hardware and software modules. For example,compiling the image group and generating the image type designators forthe images of a light-field data structure can be carried out usingappropriate software routines or modules, which can be directly loadedinto the memory of a programmable device, such as a processor, for usein a system for determining an image distribution for a light-field datastructure. Alternatively, these functions could be carried out bydedicated hardware such as a Field-Programmable Gate Array (FPGA) orApplication-Specific Integrated Circuit (ASIC).

Other objects and features of the present invention will become apparentfrom the following detailed descriptions considered in conjunction withthe accompanying drawings. It is to be understood, however, that thedrawings are designed solely for the purposes of illustration and not asa definition of the limits of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a schematic representation of an arrangement of cameras;

FIG. 2 a shows a schematic representation of a first compression scheme;

FIG. 2 b shows a schematic representation of a second compressionscheme;

FIG. 3 shows a schematic representation of a scene containing an objectof relevance;

FIG. 4 a shows a schematic representation of a number of compressionschemes compared to images of a first light-field data structure thatsatisfy a specified criterion;

FIG. 4 b shows a schematic representation of a number of compressionschemes compared to images of a second light-field data structure thatsatisfy a specified criterion;

FIG. 5 shows a block diagram of a system for performing video codingaccording to an embodiment of the invention;

FIG. 6 shows a block diagram of a video coder for coding an imageaccording to its image designation.

DESCRIPTION OF EMBODIMENTS

In the diagrams, like numbers refer to like objects throughout. Objectsin the diagrams are not necessarily drawn to scale.

FIG. 1 shows, in a schematic representation, one type of cameraarrangement for the purpose of collecting or capturing images for athree-dimensional video application. Here, the cameras are arrangedabout a scene. As already mentioned in the introduction, only a fewcameras are shown here. In reality, a much greater number of cameraswould be implemented to collect images for obtaining light-field datastructures. Images captured by the cameras are combined as describedabove to give a sequence of light-field data structures which can beused at a later point in time to render the scene from different pointsof view.

Images are ideally captured by the cameras in a synchronised manner. Forexample, sixty-four images captured at a single instant by anarrangement of sixty-four cameras can be arranged virtually as an 8×8array. After compression of the images, the image data contained in thisarray is referred to as the light-field data structure. As describedabove, storage space and/or transmission bandwidth for the light-fielddata structure can be reduced by compressing only some of the images asI-images, and the remainder as P-images. The images are compressed orcoded according to a compression scheme. FIG. 2 a and FIG. 2 b showexample compression schemes 2 a, 2 b. As explained above, the quality ofthe rendered scene requires that the I-images are evenly distributedover the light-field data structure, and that a certain number of theimages are coded as I-images. In the two compression schemes 2 a, 2 bshown, the I-images are evenly distributed, and sixteen of thesixty-four images are coded as I-images. This 8×8 array is onlyexemplary, and it will be understood that any number of cameras could beused, yielding a larger or smaller array, as appropriate.

The invention is concerned with ensuring that 3D scenes in aninteractive video application are rendered to a high level of quality.In the method according to the invention, a criterion is specified, anda compression scheme is selected that best suits the number of imageswhose contents satisfy the specified criterion. This is explained withthe aid of FIG. 3, which shows a scene in which football is beingplayed. The game is being recorded using cameras C₁, C₂, . . . , C_(n)of a camera arrangement placed around the football pitch. A football 30is being kicked about the pitch by a number of players 31, 32, 33, 34.For a future interactive 3D video application based on the game that isbeing recorded, the football 30 can be regarded as being the mostrelevant object. Therefore, at some point prior to recording the match,a criterion can be specified regarding the football 30. For example, thecriterion might be “image content contains football”. Then, any imagecaptured by one of the cameras and containing the football thensatisfies the specified criterion, while an image whose content does notinclude the football fails to satisfy the specified criterion.

The compression scheme for each light-field data structure is thenchosen on the basis of the images that satisfy the specified criterion.The way in which a compression scheme is chosen is shown visually inFIG. 4 a. Here, four different compression schemes 2 a, 2 b, 2 c, 2 dare shown, each of which fulfill the necessary quality requirements (aneven distribution of I-images, and a certain number of I-images). Thecross-hatched or shaded area overlaid on each compression scheme 2 a, 2b, 2 c, 2 d represents the images of a first light-field data structurethat satisfy the specified criterion. In the above example, these arethe images taken at a first instant that contain the football.Compression scheme 2 a provides eight I-images, compression scheme 2 bprovides 10 I-images, compression scheme 2 c also provides 10 I-images,and compression scheme 2 d provides 11 I-images. Since compressionscheme 2 d offers the most I-images that contain the football, this isthe optimal image distribution for this first light-field datastructure. The appropriate images are then coded as I-images, and therest are coded as P-images. FIG. 4 b shows the same compression schemes2 a, 2 b, 2 c, 2 d for a second light-field data structure, with imagestaken at a second instant in time. In this diagram, the shaded areaoverlaid on each compression scheme 2 a, 2 b, 2 c, 2 d represents theimages at the later time whose contents satisfy the specifiedcriterion—i.e. that contain the football. For the light-field datastructure containing these images, the best image distribution is givenby compression scheme 2 b, since this compression scheme offers the mostI-images containing the football.

FIG. 5 shows a block diagram of a system 3 for performing video codingusing the method according to the invention. Images F₁, F₂, . . . ,F_(n) captured by an array of cameras C₁, C₂, . . . , C_(n) are to becoded to give a light-field data structure 2. The type of coding to beperformed—I-image or P-image—is specified for each image F₁, F₂, . . . ,F_(n) by an image type signal T₁, T₂, . . . , T_(n) associated with theimage F₁, F₂, . . . , F_(n). The image type signals T₁, T₂, . . . ,T_(n) are generated in a system 1 for determining an optimal imagedistribution D_(opt) for the light-field data structure. Each image F₁,F₂, . . . , F_(n) captured by a camera C₁, C₂, . . . , C_(n) is analysedin a following image processing unit U₁, U₂, . . . , U_(n), where asegmentation algorithm is run on the image F₁, F₂, . . . , F_(n) todetermine whether the specified criterion is satisfied or not. Thespecified criterion is input (for instance during an initialisationstep) by means of an interface 20, such as a graphical user interface(GUI), and provided to the U₁, U₂, . . . , U_(n) using suitableparameters 21. The image processing units U₁, U₂, . . . , U_(n) eachdeliver an appropriate signal S₁, S₂, . . . , S_(n) to an image groupidentification module 11, which compiles an image group 12 or an array12 of values indicating the images F₁, F₂, . . . , F_(n) whose contentssatisfy the specified criterion (using the above example, the imagesthat contain the ball). This image group 12 is compared to a number ofpredefined reference image distributions D₁, D₂, . . . , D_(m) retrievedfrom a memory 15. The reference image distribution D₁, D₂, . . . , D_(m)that offers the most I-images for the current group 12 is selected to bethe optimal compression scheme D_(opt) for the current light-field datastructure. This optimal reference image distribution D_(opt) isforwarded to an image type designation unit 14, which generates theimage type signals T₁, T₂, . . . , T_(n) for each image. A simple binarysignal can indicate the image type, for instance a logic “1” canindicate “I-image”, while a logic “0” indicates “P-image”.

Each frame F₁, F₂, . . . , F_(n) with its associated image type T₁, T₂,. . . , T_(n) are forwarded to video coders 60. One way in which a videocoder 60 can be realised is shown as a block diagram in FIG. 6. Here, avideo coder 60 is connected to receive an the image output F₁ of thecamera C₁ comprises a module 61 for performing I-image coding using onlythe current frame F₁, and a module 62 for performing predictive codingusing the current frame F₁ as well as one or more previously storedimages. As mentioned already, previously coded P-images or I-images canbe used to code the present P-image. However, for the sake ofsimplicity, only one previously coded P-image P_(t-1) is indicated inthe diagram. The type of coding—intraframe or interframe—to be performedon the image F₁ input to the video coder 60 is specified by theaccompanying image type signal T₁. If the image F₁ has been designatedto be an I-frame, then intraframe or I-image coding is to be performed,and this is then carried out by the I-image coding module 61, using, forexample, a discrete cosine transform compression algorithm. If the imageF₁ is designated to be a P-frame, then predictive or P-image coding isto be performed, and this is carried out by the P-image coding module62, using a previously stored P-image P_(t-1) retrieved from a memory64. A copy P_(t) of the current interimage is stored in the memory 64for future use (evidently, a copy of the current I-image could be storedfor future P-image coding, if this were desired). An output multiplexer63 chooses the appropriate coder output according to the image typesignal T₁ and forwards the coded image F₁′, as part of an overalllight-field data structure, to a following application (not shown in thediagram) to be stored or transmitted, as the situation requires. The setof coded images F₁′, F₂′, . . . , F_(n)′ together give the virtuallight-field data structure 2 for the current time instant, as indicatedby the dashed loop in FIG. 5.

Although the present invention has been disclosed in the form ofpreferred embodiments and variations thereon, it will be understood thatnumerous additional modifications and variations could be made theretowithout departing from the scope of the invention. For example, the“important object” could be physically marked in some way, for instanceby painting it with a substance which is visible in the ultravioletregion of the spectrum, and equipping the cameras with an additionalultraviolet filter. The segmentation algorithm that is used to analysethe images need then only scan the images for the appropriate shape.

For the sake of clarity, it is to be understood that the use of “a” or“an” throughout this application does not exclude a plurality, and“comprising” does not exclude other steps or elements. A “unit” or“module” can comprise a number of units or modules, unless otherwisestated.

The invention claimed is:
 1. A method of determining an imagedistribution for a light field data structure, which method comprisesobtaining a plurality of images from a plurality of image sources;performing image analysis on each image of the plurality of images todetermine whether a specified criterion is satisfied by content of thatimage; identifying a group of images whose contents satisfy thespecified criterion; comparing the group of images to each referenceimage distribution of a set of predefined reference image distributionsto select an optimal image distribution, wherein a reference imagedistribution includes a predefined arrangement of I-images and P-imagesof the light field data structure; and designating each image of theplurality of images of the light field data structure to be either anI-image or a P-image according to the selected image distribution. 2.The method according to claim 1, wherein the specified criterionincludes parameters related to an object to be detected in content of animage.
 3. The method according to claim 1, wherein the step ofidentifying a group of images includes compiling an image-related arraybased on the images that satisfy the specified criterion.
 4. The methodaccording to claim 1, wherein the optimal image distribution correspondsto the reference image distribution which provides a greatest number ofI-images for the image group.
 5. The method according to claim 1,wherein the step of performing image analysis includes running asegmentation algorithm on that image.
 6. A method of performing videocoding of a light field data structure, which method comprisesdetermining an optimal image distribution for images of the light fielddata structure using the method of claim 1; coding each image designatedto be an I-image using a compression algorithm; and coding each imagedesignated to be a P-image using a previously coded image.
 7. A systemfor determining an image distribution for a light field data structure,comprising a plurality of image sources for obtaining a plurality ofimages; an image analysis module for performing image analysis on eachof the plurality of the plural images to determine whether a specifiedcriterion is satisfied by content of that image; an image groupidentification module for identifying a group of images whose contentssatisfy the specified criterion; a comparison module for comparing theimage group to each reference image distribution of a set of predefinedreference image distributions to select an optimal image distribution,wherein a reference image distribution includes a predefined arrangementof I-images and P-images of the light field data structure; and an imagedesignation module for designating each of the plural images of thelight field data structure to be either an I-image or a P-image based onthe selected image distribution.
 8. A system for determining an imagedistribution for a light field data structure according to claim 7,further comprising an interface for specifying a criterion.
 9. Anon-transitory computer readable medium encoded with data andinstructions that when executed by a computer causes a computer to:obtain a plurality of images from a plurality of image sources; performimage analysis on each image of the plurality of images to determinewhether a specified criterion is satisfied by content of that image;identify a group of images whose contents satisfy the specifiedcriterion; compare the group of images to each reference imagedistribution of a set of predefined reference image distributions toselect an optimal image distribution, wherein a reference imagedistribution includes a predefined arrangement of I-images and P-imagesof the light field data structure; and designate each image of theplurality of images of the light field data structure to be either anI-image or a P-image according to the selected image distribution.
 10. Asystem for performing video coding, comprising: a system for determiningan image distribution for a light field data structure comprising: aplurality of image sources for obtaining a plurality of images; an imageanalysis module for performing image analysis on each of the pluralityof the plural images to determine whether a specified criterion issatisfied by content of that image; an image group identification modulefor identifying a group of images whose contents satisfy the specifiedcriterion; a comparison module for comparing the image group to eachreference image distribution of a set of predefined reference imagedistributions to select an optimal image distribution, wherein areference image distribution includes a predefined arrangement ofI-images and P-images of the light field data structure; and an imagedesignation module for designating each of the plural images of thelight field data structure to be either an I-image or a P-image based onthe selected image distribution; an I-image coder for coding an image,designated to be an I-image, using a compression algorithm; and aP-image coder for coding an image, designated to be a P-image, using apreviously coded image.